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Pretherapeutic Identification of High Risk DLBCL Patients



G.Valet1), H.G.Höffkes2)

2) Max-Planck-Institut für Biochemie, Martinsried,
1) Medizinische Klinik III, Klinikum Fulda, Germany



1. Background: Diffuse large-B-cell lymphomas (DLBCL) represent the most frequent lymphoma in adults. Between 35 to 40 % of patients are cured by anthracyclin therapy. The relatively high therapeutic failure rate may be explained by the existence of subgroups of lymphomas with responsivenes to other chemotherapeutic agents.
- The study of gene-expression profiles permitted the characterization of a germinal-center B-cell-like subgroup with good therapy response and of the activated B-cell-like subgroup with poor outcome. Recent external links gene expression profiling (L3) using "Lymphochip" arrays (7399 gene spots) has permitted to characterize the additional type3 large B-cell lymphoma by an hierarchical clustering algorithm. A method was developed to predict the likelihood of survival after chemotherapy for diffuse large B-cell lymphoma. This predictor of prognosis and the international prognostic index (IPI) are independent prognostic indicators.
- The data have been reanalyzed by fuzzy neural network in combination with the SWEEP operator method. An overall accuracy of 72% correct decisions was obtained (L2).

2. Goal: Predictors of prognosis are patient group oriented and valuable for therapeutic patient stratification. They are, however, not informative as outcome predictors for individual patients prior to an envisaged chemotherapy.
- The goal of a study on the above data is directed towards the pretherapeutic identification (>95% correct) of high risk DLBCL patients by a data sieving algorithm

3. Results: Present results suggest that predictive identification for individual patients are possible and that predictive (fig.1) and prognostic (fig.2) data patterns are different although a certain number of lymphocyte associated parameters are selected in both cases. Eight of the differentially expressed genes in the predictive pattern concern genes of unknown function. This seems of particular interest for further studies on gene regulation in DLBCL.

4. Conclusion: The classification of the reported data suggest that individualized pretherapeutic risk assessment for patient survival is possible (L1).

Literature References:
L1 Valet G, Höffkes HG. Data pattern analysis for the individualised pretherapeutic odentification of high-risk diffues large B-cell lymphoma (DLBCL) patients by cytomics. Cytometry Part A 59A:232-236(2004) -external link (PDF)
L2 Ando T, Katayama M, Seto M, Kobayashi T, Honda H. Selection of causal genes sets from transcriptional profiling by FNN modeling and prediction of lymphoma outcome. Genome Informatics 13:278-279(2002)
L3 Rosenwald A, Wright G, Chan WC, Connors JM, Campo E, Fisher RI, Gascoyne RD, Müller-Hermelink HK, Smeland EB, Staudt LM. The use of molecular profiling to predict survival after chemotherapy for diffuse large B-cell lymphoma. NEJM 346:1937-47(2002) -external link (PDF)


© 2017 G.Valet
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Last Update: Jan 02,2012